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Ming Ding

24 papers hereh-index 2311.6k citations30 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author20

Across the 21 of 24 papers where every author was matched, so the position is known.

fields
  • cs.CV14
  • cs.CL5
  • cs.LG4
  • cs.AI1
same name
  • Ming Ding — 66 papers, h 40
  • Ming Ding — 41 papers, h 37
  • Ming Ding — 29 papers, h 23
  • Ming Ding — 10 papers, h 7
  • Ming Ding — 9 papers, h 3
  • Ming Ding — 6 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192024
most citedGCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

787 citations · 1.6k across the 22 of their papers we have counts for

collaborators
Showing 2023 · cs.CVShow all

4 papers · 2 filters

cs.CV2023★ 6 cited

CogAgent: A Visual Language Model for GUI Agents

Wenyi Hong, Weihan Wang, Qingsong Lv +11

People are spending an enormous amount of time on digital devices through graphical user interfaces (GUIs), e.g., computer or smartphone screens. Large language models (LLMs) such…

cs.CV2023★ 77 cited

CogVLM: Visual Expert for Pretrained Language Models

Weihan Wang, Qingsong Lv, Wenmeng Yu +13

We introduce CogVLM, a powerful open-source visual language foundation model. Different from the popular shallow alignment method which maps image features into the input space of…

cs.CV2023★ 5 cited

Relay Diffusion: Unifying diffusion process across resolutions for image synthesis

Jiayan Teng, Wendi Zheng, Ming Ding +4

Diffusion models achieved great success in image synthesis, but still face challenges in high-resolution generation. Through the lens of discrete cosine transformation, we find the…

cs.CV2023★ 99 cited

ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation

Jiazheng Xu, Xiao Liu, Yuchen Wu +5

We present a comprehensive solution to learn and improve text-to-image models from human preference feedback. To begin with, we build ImageReward -- the first general-purpose text-…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.